Key Driver Analysis (Diagnostic insights)

Key driver analysis is a statistical method used to identify and understand the factors that significantly affect a metric, as well as the extent to which these factors impact the outcome. This analysis helps uncover the causes and the underlying drivers of observed trends in the target metric.

• Configuring Key Driver Analysis
• Viewing and interpreting the results of Key Driver Analysis

Configuring Key Driver Analysis

1. Open the desired chart, and click the Settings icon at the top right corner.

   

2. Navigate to the Zia Insights tab and expand the Key Driver Analysis section.

   

3. Select the Show Key Drivers for the Diagnosable Insights checkbox.

   

4. Choose a Measure (target) column for which you want to evaluate the outcome from the Select Measure drop-down.

   

5. Once you've chosen a measure column, all relevant factors that may influence it will be automatically populated in the text box below. However, you can add more factors by clicking the + Add Column link at the bottom. You can add a maximum of five dimension columns and three measure columns.

   

6. Click the Show Top N Drivers drop-down to select the number of influential factors you want to consider for analysis. You can choose between 1 and 5 factors(drivers) from the from the set of factors added above.

   

7. You can also choose the number of values of each factor to be considered for analysis using the Top N Factors drop-down next to each factor. By concentrating on these top values, the analysis can reveal the key drivers that have the most substantial impact on the outcome you’re assessing. In the pop-up that appears, the following options are available.
   • Top Factors: Select the number of top contributing values from each factor to analyze their influence on the target measure column.

     

   • Actual Values: Select the values to be considered from each factor to analyze their influence on the target measure column.

     

8. Once you have configured the settings, close the settings dialog and click Save to save the changes made.

   

Viewing and interpreting the results of Key Driver Analysis

Key Driver Insights (Diagnostic Insights) deliver valuable analysis of time series trends, revealing the underlying factors behind increases or decreases. They clarify the drivers of change, making it easier to understand the reasons behind shifting patterns over time.

To view the diagnostic insights, click the Diagnosis icon that appears on the Time Series Insights in the Zia Insights dialog.

In the dialog that appears, you can view the diagnostic insights divided into the WHAT and WHY sections.

WHAT Section

It offers an overview of the current state of the measure column, detailing:

• The observed trend of the measure column, indicating whether it is increasing or decreasing.
• A breakdown of the factors influencing changes in the measure column, including the percentage impact of each factor on its overall rise or fall.

WHY Section

It details all the potential reasons for the observed trend, including in-depth impact assessment and the various factors contributing to the current outcome. Click the Know More link to access the diagnostic insights, which may vary depending on the report data.

Impact

The Impact section refers to the influence or contribution of a specific factor (driver) on the target measure column. It quantifies the extent to which that factor affects the outcome being analyzed.

Possible Reasons

The Possible Reasons section outlines all the factors that may have contributed to the observed trends in the target measure column, including:

• Top contributors are the factors or drivers that positively influence the target measure, resulting in its increase.

  

• Top offsetters, on the other hand, are factors that negatively affect the target measure, leading to a decline.
• Anomaly Insights identify unusual spikes or drops in the target measure that deviate from expected trends.

  

• Trends and Relationships analysis between the target measure and influencing measures reveals whether there is an increasing or decreasing trend. It also determines the type of correlation, whether direct or indirect, and offers prescriptive recommendations to sustain or enhance the observed trend.
• Occurrence analysis focuses on identifying how frequently specific drivers or factors impact an outcome, helping to understand the significance and effect of each driver over time or across different segments.

Missing Drivers

The Missing Drivers section highlights potential factors or variables that could significantly influence the target measure but have not been included in the analysis. Zia insights considers these drivers and assesses their potential impact on the target measure column.

• A factor positively impacts the target measure column if an increase in that variable results in an increase in the target measure column.
• A factor negatively impacts the target measure column if a decrease in that variable results in a decline in the target measure column.